GVLQA (Graph Vision-Language Question-Answering)

GVLQA is the first vision-language QA dataset for general graph reasoning. Contains a base set GVLQA-BASE and four image-augmented subsets GVLQA-AUGLY, GVLQA-AUGNO, GVLQA-AUGNS, GVLQA-AUGET, where the samples are relatively corresponding with the base set. Contains 7 graph reasoning tasks: detecting cycle, connectivity, computing topological ordering, shortest path, maximum flow, bipartite matching num, and Hamilton path. Utility: 1) evaluate the graph reasoning capabilities of VLMs or LLMs; 2) help models acquire fundamental graph comprehension and reasoning abilities as a pretraining dataset.